Real-time detail highlighting on 3D models

ABSTRACT

A dental CAD/CAM application generates a 3D model representing a patient&#39;s dental anatomy. This model may be a 3D surface. The surface may also be textured with either a monochrome or color image superimposed. The display routine that is used to display the 3D model is enhanced to adjust the contrast in the region of a displayed mouse pointer (or other input device) as a user explores the display image. When this feature is activated and the mouse pointer positioned, preferably the texturing on the 3D model is recomputed in that local area and redisplayed showing greater contrast and detail. Preferably, the contrast is increased from a center to an edge of the area of contrast. Having the texturing of the model being improved and highlighted around the margin is desirable, as it allows the user to see more easily where the margin is located.

BACKGROUND OF THE INVENTION

Technical Field

This disclosure relates generally to computer-assisted techniques forcreating dental restorations.

Brief Description of the Related Art

During the last decade various technological advancements haveincreasingly started to be applied to systems in the healthcare arena,particularly in dental care. More specifically for example, traditionalimaging and computer vision algorithms coupled with soft X-ray sensitivecharge coupled device (CCD) based vision hardware have renderedconventional X ray photography ubiquitous, while more advanced dataimaging and processing has enabled passive intraoral 3D topography. Thelatter comprises the acquisition portion of a CAD/CAM system, whichwould typically be followed by a design step using some sort ofmanipulating software, and a manufacturing step that might entail anoffice laser printer-sized milling machine. The entire system allows adentist to provide a patient the same services a manufacturinglaboratory would provide with a certain turnaround time, however, allchair-side and on-the-spot, greatly reducing the possibility ofinfections and discomfort to the patient. In addition, clinical casescontaining raw and processed data are easily shared as digital filesbetween dentists who lack the second portion of the system, i.e. themanufacturing step, and laboratories who have adapted and evolved toembrace CAD/CAM.

In a clinical case where a patient is required a crown, for example,traditionally the dentist would prepare the area, and take a physical(active) impression using a silicone-based agent, thereby subjecting thepatient to some discomfort during the process. The next step requiresthe dentist to place a temporary crown over the area and then schedulethe patient for an additional visit once the final crown based on theoriginal impression has been manufactured by a laboratory. During thistime, the patient is more subject to local infections. The entireprocess of mold-taking and re-shaping of materials at the laboratory isinvolved, is rather cumbersome and outdated, and it contains severalsteps that must be controlled by tight tolerances.

Intraoral, in-vivo passive 3D scanning is a rather challenging task. Amultitude of technical and economic factors impose numerous constraintsand add difficulties to the problem. For these reasons, successfulsystems must address and solve all these challenges, rendering them muchmore complex than otherwise conceptually simple 3D scanners. First,consider the operating environment, i.e. intraoral on a live patient.Digital imaging complications arise due to the restricted operatingvolume imposing a certain arrangement of optics and sensors such as tofacilitate practical system operation in-vivo and intraoral as a probingdevice. Further, this environment is dark, contains air with a highdegree of relative humidity expunged from the patient's lungs with everybreath, and it facilitates artifact contamination of areas of interestby the mere presence of saliva, air bubbles within it and the patient'stongue itself. In addition, the environment is not static, as thepatient is not a still unanimated object.

Second, consider the operator, i.e. the dentist. The device must beergonomically designed around the system to ensure it is a useful tooland can solve the problem. Power consumption and power dissipation areimportant considerations. Moreover, as a hand-held medical device, itmust pass additional regulatory affairs imposed by governmentauthorities, as well as comply with the local standard electromagneticinterference/emission laws.

Third, consider the quality of the data obtained in the scanningprocess; if not comparable or better with current active (i.e. mold)impression-taking, the whole process is rendered null. The quality andaccuracy of the data must also be consistent with the requirements ofthe CAM step of the process. Ultimately how well a milled restorationfits a patient's preparation area is a function of all of these factors.

There are several commercially-available solutions, including systemsthat integrate the CAM component. Some solutions still rely on contrastenhancing agents applied as a spray on the preparation area to mitigatesome of the difficulties of imaging intra orally in-vivo. The 3Dscanning implementations available employ several methods for obtainingsurface topography estimations. These range from solutions exploitingdepth map generation by confocal imaging, to fringe projection assisted3D imaging, although other approaches such as correspondence-assistedstereoscopic imaging or plenoptic imaging may be used. Typically, thehighest degree of data accuracy and ease of use, coupled with theeconomics and availability of off the shelf components, is greatlyfacilitated by employing a structured light projection technique, suchas provided by a commercial system such as E4D Dentist, from E4DTechnologies, LLC, of Dallas, Tex.

BRIEF SUMMARY

A dental CAD/CAM application generates a 3D model representing apatient's dental anatomy. This model may be a 3D surface, for example, asurface composed of connected triangles where each triangle is made upof three 3D points along with a normal. The surface may also be texturedwith either a monochrome or color image superimposed on that surface.Typically, the texture is created by a camera image overlaid on top ofthe 3D model. According to this disclosure, the software display routinethat is used to display the 3D model is enhanced to adjust the contrastof the texture in the region of a displayed mouse pointer (or otherinput device) as a user explores the display image. This contrastenhancement feature may be activated by a default configuration setting,or it may be selected. When this feature is activated and used (with thetextured 3D model displayed on the screen), wherever the mouse pointeris positioned, preferably the texturing on the 3D model is recomputed inthat local area and redisplayed showing greater contrast and detail.Preferably, the contrast is increased from a center to an edge of thearea of contrast. Having the texturing of the model being improved andhighlighted around the margin is desirable as it allows the user to seemore easily where the margin is located.

The foregoing has outlined some of the more pertinent features of thesubject matter. These features should be construed to be merelyillustrative.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the disclosed subject matter andthe advantages thereof, reference is now made to the followingdescriptions taken in conjunction with the accompanying drawings, inwhich:

FIG. 1 illustrates basic components and geometry underlying 3Dtriangulation;

FIG. 2 is a known technique to project laser pattern lines onto apreparation area using an intra-oral hand-held wand device;

FIG. 3 illustrates a 3D generated model created by processing thepartially-illuminated pattern lines;

FIG. 4 illustrates an optical sub-system of an intra-oral scanningdevice of this disclosure with its outer housing removed;

FIG. 5 is an elevation view of the intra-oral scanning device of thisdisclosure illustrating a removable tip that includes a heating element;

FIG. 6 is an embodiment of system architecture to control the hand-heldintra-oral device of this disclosure;

FIG. 7 illustrates a preferred 3D pipeline processing approachimplemented in the device;

FIG. 8 illustrates the rendering of a textured 3D model juxtaposedagainst a live video feed provided by the scanning techniques of thisdisclosure;

FIG. 9 is an elevation view of the scanning device;

FIG. 10 depicts a contrast enhancement function according to thisdisclosure; and

FIG. 11 depicts various functional modules of the contrast enhancementfunction.

DETAILED DESCRIPTION

The principles behind structured light based 3D triangulation areexplained in various works. The underlying principles are described withrespect to FIG. 1, which illustrates a light source 100 directed to anobject 102, with the reflection being captured a charge coupled device(CCD) imaging surface 104. This illustrates the basic components andprinciples behind 3D triangulation in an intuitive manner. In thisapproach, a change in height due to object topography is registered as adeviation of a projected point onto a charge coupled device (CCD)imaging surface. In operation, a laser pattern is projected with thehelp of an LCOS (i.e. liquid crystal on silicon) device. In particular,a sequence of a set of lines is generated by the lines reflected fromLCOS to form a set of planes, or, if distortion is involved (astypically is the case when implemented), a set of conical or ruledsurfaces.

FIG. 2 illustrates a pattern projected onto a preparation area. In ananalogous manner, each point in the camera CCD frame corresponds to aline in space that passes through the imaging center or focal point.Because preferably the LCOS and the camera are laterally separated, thepoint of intersection between each laser surface generated by a singleLCOS pixel and each line of sight is well-defined. Thus, by knowing thepixel coordinates on the camera matrix and the shape of the lasersurface, it is possible to obtain coordinates of a 3D pointcorresponding to that pixel. When laser lines are projected onto thesurface of the scanned object, the image of those lines in the cameraplane defines a set of 3D points corresponding to the object surface. Toobtain the shape of the surfaces formed to each laser line, acalibration procedure is performed. A camera lens calibration isperformed by taking an image of a checkerboard pattern, with a set ofintrinsic camera parameters (such as focal length and lens distortion)estimated as a result. From this, an exact direction of a raycorresponding to each camera pixel is established. To determine theshape of the laser surfaces, a set of planes located at the knowndistances with known orientation are scanned. Each line projected ontoeach successive plane forms an image on the CCD matrix, represented as aset of pixels and, because for each pixel the corresponding directionand the actual distance to the calibration plane are known, the set of3D coordinates forming a line of intersection between a laser surfaceand calibration plane are known as well. Interpolation betweensuccessive lines produces the shape of the laser surface, represented bythe final generated 3D model shown in FIG. 3.

The frames used to capture the data for the 3D model arepartially-illuminated frames (such as shown in FIG. 2, wherein the LCOSpaints a series of lines in a pattern). To facilitate the operation ofthe device and provide live video as feedback to the operator (as wellas the 3D-computed data), a preferred implementation uses a sequence ofpatterns throughout which full illumination frames are selectivelyinterspersed. A full illumination frame involves all or substantiallyall lines being turned on, as compared to the partially-illuminatedapproach shown in FIG. 2, wherein only some lines are projected. In afull illumination frame, in effect there is no pattern. Thepartially-illustrated frames provide the data from which the 3Dcoordinates of the surface are determined. A technique for renderingframes in this manner is described in U.S. Pat. No. 7,184,150, thedisclosure of which is incorporated herein by reference. In contrast,the full illumination frames are used for texturing the 3D modelgenerated by the partially-illuminated frame data. In one sequence, afirst set (e.g., six) pattern frames are used, interspersed with asecond set (e.g., three) illumination frames, for a sequence total ofnine total CCD frames. A software traffic shaper is then used toseparate captured frames in two streams, namely, a live preview stream,and a data processing stream from which the 3D model is generated. Ifnecessary, e.g., for computational or storage efficiencies, the livepreview stream can give up priority and drop some frames when the CPUwork load exceeds a certain limit.

In the embodiment described above, the same light source (e.g., a bluelaser) is used to generate both the first series of frames and thesecond series of (interleaved) frames, and a monochrome sensor is used.If it is desired to output a color video preview, one or more otherlight sources (e.g., a red laser, a green laser, or some combination)are used to vary the color of the full illumination frames. Thus, in onealternative embodiment, there are three different light sources (blue,red and green), with the resulting data returned from these fullillumination frames then being used to provide a color video preview. Asyet another alternative, full illumination frames are generated using asource of monochrome light, and a color sensor is used to receive thereflected data (to generate the color video preview). Still anotheralternative to generate a color video image is to use full illuminationred and green frames with a partial illumination blue frame. Other lightsources (e.g., a red/green laser or even an LED) may obviate the fullillumination blue frame. Another possibility is to use red as theadditional color (leaving out the green, or vice versa), and thenprocessing the resulting data to generate a pseudo-color video stream.When the approach uses the red, green and blue laser, the scanner may beused to generate a simplified optical coherence tomography (OCT) scanusing discrete lasers instead of a single broadband source, or a sweptsource.

FIG. 4 illustrates an embodiment of an optical sub-system of anintra-oral device with its outer housing removed. The primary imagingcomponents of the optical sub-system 400 include a laser 402, a cylinderlens 404, a speckle reduction diffuser 406, an aperture 408, a reflector410, a condenser lens 412, a beam splitter 414, a quarter wave plate415, the LCOS device assembly 416, a projection lens barrel assembly418, and a polarized lens 420. A return (imaging) path comprises imaginglens barrel assembly 422, first and second imaging reflectors 424 and426, and the CCD sensor 428.

Without meant to be limiting, a preferred laser is a blue laser devicewith a wavelength of 450 nm, and thus the optical path for theprojection side is polarization-based. In this embodiment, projection isachieved with the LCOS device 416 having a resolution of 800 by 600pixels and a pixel size of 8.0 um. The speckle reduction diffuser (ade-speckle component) is used to eliminate the speckle issues otherwisecaused by using a laser as the light source. Using a laser (instead of,for example, an LED light source) produces a much brighter projectedpattern which, in turn, allows the scanner to image intra-orally withoutpowder.

As seen in FIG. 5, the intra-oral device 500 is configured as ahand-held wand that includes a tip portion or “tip” 502. FIG. 9illustrates an embodiment of the wand with the outer housing present. Asseen in FIG. 5, the tip 502 includes a mirror 504 and preferably noadditional glass windows; the mirror 504 reflects the projection pathfrom a long axis of the device (the optical sub-system shown in FIG. 4)towards the target area being scanned, and that receives the imagingpath data returned from the target area. The returned data is forwardeddown the long axis of the device, where it is imaged by the CCD sensordevice. By using a mirror 504 in the tip 502, the possibility of asurface near the target area being contaminated with dirt or fluid isreduced. This is desirable, as any contamination on a glass window orprism surface may be close to (or within) a focused region of theoptical path, and therefore may result in erroneous measurements. Thereflecting mirror 504 is outside the focus region, and thus any slightimperfections or debris on its surface will not result in erroneous datameasurements. Preferably, the tip 502 is removable from the rest of thewand housing, and the mirror is heated (with an active heating element506) to prevent fogging of the optical surfaces while the device isbeing deployed intra-orally. The heating element may be a metalconductive element that is supported in a molded plastic housing andthat receives current from other wand electronics. Any other type ofheating element may be used. FIG. 9 illustrates the removable tip 902.In this manner, multiple tips (the others now shown), each with varyingmirror angles and sizes, may be implemented with a single wand body thatincludes the optical sub-system shown in FIG. 4. In this manner,different tips may be used for different scanning scenarios, such asscanning posterior preparations in small patients, or more challengingsituations where a steeper viewing angle is required.

FIG. 6 illustrates system architecture for the wand. In thisimplementation there are three (3) subsystems, namely, an imagingsub-system, a projection/illumination sub-system, and a peripherysub-system. Preferably, imaging is achieved by an over-clocked dual-tapCCD with an active resolution of 648 by 484 pixels, and a pixel size of9 um.

In this embodiment, which is not intended to be limiting, the systemarchitecture comprises a tightly-integrated IP FPGA core containing anIEEE 1394b S800 link layer, CCD/ADC synchronizers, the LOCS andillumination synchronizer. Cross-clock domain FIFOs are implemented tosynchronize the CCD exposure/LCOS projection/CCD readout sequence to theIEEE1394 bus clock, which is 125 us or 8000 Hz. The FPGA is assisted byan ARM processor, implementing the IEEE1394b transaction layer andvarious housekeeping system tasks, such as running an I2C peripherypriority task scheduler. The FPGA implements deep FIFOs for asynchronouspacket reception and transmission and likewise for the CCD video data,which is sent as isochronous packets. It also implements a prioritizedinterrupt mechanism that enables the ARM processor to de-queue anden-queue IEEE1394 asynchronous packets and to complete them according tothe bus transaction layer specification and various applicationrequirements. The bulk of the housekeeping work in the system originatesin user space software, ends up as an asynchronous packet in the ARMprocessor and is dispatched from there through either I2C or SPI to theappropriate peripheral component. The software is designed to maintainthe hardware pipelining while running within a non-real time operatingsystem (OS), such as Microsoft® Windows 7 and Apple® OS/X. Otheroperating systems such as Android or iOS® may be used.

In this embodiment, and to provide the required data quality at adesired rate, the imaging system preferably is comprised of a slightlyover-clocked dual tapped CCD. The CCD is 680 by 484 pixels containingsome dark columns and rows for black offset correction and is specifiedto have 57 dB of dynamic range at a pixel clock of 20 MHz with a maximumpixel clock of 30 MHz. The projection and illumination subsystemcomprises LCOS device, a laser diode driver, a 450 nm blue laser diodeand an optical de-speckling device. As illustrated in FIG. 7, preferablydata is processed in a pipeline distributed across several computingresources. In this approach, data from the CCD ADCs, 8 bit per pixel, isfirst run through a tap matching block where both taps are linearizedand matched according to a look up table. This implies a previouscalibration step. The traffic shaper separates the data into livepreview and 3D processing input frames. The 3D processing input framescontain projected patterns. On the GPU these frames are first runthrough a centroid detector implemented as a recursive sub-pixel edgedetector, a correspondence block, and finally a point cloud generationblock. This output is then run on the CPU side through a bilateralfilter for data smoothing, and through an alignment block to stitchscans together. This processing distribution allows for runningalignment in a pipelined fashion with 3D point cloud generationhappening in parallel.

Preferably, fast imaging is used to allow minimization of errors (e.g.,due to operator hand jitter). In one embodiment, good results wereobtained with a live preview window of approximately 20 frames persecond, coupled with approximately 15 frames per second for the 3D data.

A representative display interface is used to display the 3D model, onthe one hand, and the live video preview window, on the other. FIG. 8illustrates a representative screen grab from a juxtaposition of theseviews. These views may be juxtaposed in any convenient display format(e.g., side-by-side, above-below, as an overlay (or “3D texture” view),or the like).

Real-Time Detail Highlighting on 3D Models

In dental CAD/CAM applications as described above, a 3D model may beprovided representing the upper or lower arches. This model may be a 3Dsurface, for example, a surface composed on connected triangles whereeach triangle is made up of three 3D points along with a normal. Thesurface may also be textured with either a monochrome or color imagesuperimposed on that surface. A technician may use this model to designa restoration that may subsequently be manufactured. As part of thatdesign, the technician may be required to locate and identify certainfeatures on that model. For example, the technician may be required toidentify the margin on a preparation so that a subsequently designedrestoration will contact at that margin, which is a clinicalrequirement. This margin may be identified as an edge in the case of asupergingival margin, or it may be identified as a change in texture inthe case of an equigingival margin. In the latter case, the edge can bedetected by looking for a color or intensity difference between theprepared tooth and the adjacent gingiva. These types of 3D models aremost easily obtained through the use of an intra-oral scanner describedand depicted above, such as the Planmeca PlanScan. A 3D intra-oralscanner is able to obtain 3D surface information as well as capturemonochrome or color images that can then be superimposed on the 3Dmodel. Because of varying lighting conditions in the oral cavity and theneed to obtain a single model with uniform texturing, the multiplemonochrome or color images are blended together. The drawback to this isthat in some cases there is a loss of contrast locally because of theblending that occurs. The subject matter herein is intended to mitigateagainst this loss of contrast by allowing the user of the CAD/CAMsoftware to locally “see” the original high contrast area.

To this end, and according to this disclosure, the software routinesthat are used to display the 3D model are enhanced to improve thecontrast in the region of the displayed mouse pointer. This contrastenhancement feature may be activated by a default configuration setting,or it may be selected. When this feature is activated and used (with thetextured 3D model displayed on the screen), wherever the mouse pointeris positioned, preferably the texturing is recomputed in that local areaand redisplayed showing greater contrast and detail. This is veryuseful, for example, during the process of identifying the margin on apreparation. As depicted in FIG. 10, the mouse pointer 1000 is typicallyused to select the margin curve 1002 on the 3D surface 1004. When thisoperation is selected, an area of enhanced contrast 1006 is displayed.Preferably, the contrast is increased from a center to an edge of thearea of contrast. Thus, by having the texturing of the model beingimproved and highlighted around the margin allows the user to see moreeasily where the margin is.

The following is one preferred algorithm for implementing thisfunctionality. The routine begins with the user moving the mouse pointerto a new location. Using standard techniques, e.g., by creating a raybased on the camera position and the mouse position and intersecting itwith the 3D surface, the 3D location on the 3D surface is determinedfrom the mouse pointer position on the screen. The image capture routinethen obtains all (or substantially all) of the close 3D vertices aroundthat 3D location (for example, all points within a sphere centered aboutthat point and out to a certain radius). Close points preferably arefound by doing a nearest point search in a K-D tree. Statistics (such asmean intensity and standard deviation of intensities) are then gatheredfor those collected vertices. If there is a monochrome image draped onthe surface, for example, a preferred approach is to collect statisticson the range of intensities that are present. If a color image is drapedon the surface, the same process can be repeated for each color channel.The routine preferably computes the mean and standard deviation for thegathered statistics. Based on the statistics, the routine then adjuststhe properties of the GPU graphics shaders (see FIG. 7) to provide agreater contrast in the area of the location. Essentially, the techniqueprovides for histogram stretching by adjusting the standard deviation,then traversing the points and adjusting their intensity based on thenew standard deviation to change the contrast. For example, in the caseof a monochrome texture, the routine offsets the fragment intensity bythe difference between the mean and standard deviation and scale theinverse by the standard deviation. The aforementioned statistics arefiltered in order to give a smooth appearance. This processing adjuststhe gain and/or level parameters in the shaders. In the case of a colortexture, preferably the same process is performed for each colorchannel; in the alternative, the routine forces the local visualizationto be monochrome, or changes the colors to highlight the differences.

Essentially, the technique provides for histogram stretching byadjusting the standard deviation, then traversing the points andadjusting their intensity based on the new standard deviation to changethe contrast.

The above process describes the gathering of statistics for a singlepoint and the resulting display of the highlighted area around the mousepointer. Optionally, the technique may involve continuing to gatherstatistics as the mouse pointer is moved and maintaining a temporal meanand standard deviation of the statistics being gathered. The effect inthat case is to improve the real-time visualization as the user movesthe mouse pointer.

Another variation of the technique is to local adjust the 3D graphicslighting parameters to exaggerate shadows and thus detail in the regionsurrounding the mouse pointer.

Another variation of the technique is to adjust local 3D geometry in theregion surrounded the mouse pointer to exaggerate 3D features. In thiscase, for example, the algorithm described above would proceed asdescribed but the statistics gathered would be related to the 3D surfaceand not to the texturing. So, for example, normals of the pointsgathered could be analyzed and then the geometry adjusted locally inthat region to produce a more marked variation in the normals (and thushighlighting details).

This process can also be used for different ways the user can direct apointer on the screen, including touch pads, touch screens, pens andgestures.

The adjustment to contrast may be carried out in circumstances otherthan when the mouse cursor is positioned or re-positioned. In onealternative, a keyboard shortcut may be used to control the operation.

The local area of contrast need not be limited to a circular region suchas depicted in FIG. 10. The area may have other configurations, and thedegree of contrast change within the area may be varied (as describedabove) or uniform.

The techniques herein may be used to adjust contrast for displaysurfaces other than the texture itself.

FIG. 11 depicts the various functions that are implemented to providethe real-time detail highlighting operation of this disclosure. Asdescribed above, the operation assumes that a 3D model (generated from adata capture) is being rendered on the display, together with a texturesuperimposed on a surface of the 3D model. Typically, the texture is ais a monochrome image, or a color image overlaid on the 3D model. Asdepicted in FIG. 11, the data 1100 representing the 3D model is input toan intersection manager 1102, and the data 1104 representing the textureimage is input to a statistics calculator 1106. Cursor position data1108 and camera orientation/position data 1110 (for the texture image)are supplied to a ray generator 1112. The ray generator 1112 outputs aray to the intersection manager 1102, which outputs a 3D point to thestatistics calculator 1106. The output of the statistics calculator 1106drives the GPU shaders 1114 as described to generate the contrastadjustments 1116.

More generally, the display method is implemented using one or morecomputing-related entities (systems, machines, processes, programs,libraries, functions, code, or the like) that facilitate or provide theabove-described functionality. Thus, the wand (and its systemarchitecture) typically interface to a machine (e.g., a device ortablet) running commodity hardware, an operating system, an applicationruntime environment, and a set of applications or processes (e.g.,linkable libraries, native code, or the like, depending on platform),that provide the functionality of a given system or subsystem. Theinterface may be wired, or wireless, or some combination thereof, andthe display machine/device may be co-located (with the wand), or remotetherefrom. The manner by which the display frames are received from thewand is not a limitation of this disclosure.

In a representative embodiment, a computing entity in which the subjectmatter implemented comprises hardware, suitable storage and memory forstoring an operating system, one or more software applications and data,conventional input and output devices (a display, a keyboard, agesture-based display, a point-and-click device, and the like), otherdevices to provide network connectivity, and the like.

Generalizing, the intra-oral digitizer wand of this disclosure isassociated with the workstation to obtain optical scans from a patient'sanatomy. The digitizer scans the restoration site with a scanning lasersystem and delivers live images to a monitor on the workstation. Thetechniques of this disclosure thus may be incorporated into anintra-oral digital (IOD) scanner and associated computer-aided designsystem, such as E4D Dentist™ system, manufactured by D4D Technologies,LLC. The E4D Dentist system is a comprehensive chair-side CAD CAM systemthat produces inlays, onlays, full crowns and veneers. A handheld laserscanner in the system captures a true 3-D image either intra-orally,from impressions or from models. Design software in this system is usedto create a 3-D virtual model.

Generalizing, a display interface according to this disclosure isgenerated in software (e.g., a set of computer program instructions)executable in at least one processor. A representative implementation iscomputer program product comprising a tangible non-transitory medium onwhich given computer code is written, stored or otherwise embedded. Thedisplay interface comprises an ordered set of display tabs andassociated display panels or “viewports.” Although the illustrativeembodiment shows data sets displayed within multiple viewports on asingle display, this is not a limitation, as the various views may bedisplayed using multiple windows, views, viewports, and the like. Thedisplay interface may be web-based, in which case the views of displayedas markup-language pages. The interface exposes conventional displayobjects such as tabbed views, pull-down menus, browse objects, and thelike.

Although not meant to be limiting, the technique described above may beimplemented within a chair-side dental item CAD/CAM system.

While the above describes a particular order of operations performed bycertain embodiments of the described subject matter, it should beunderstood that such order is exemplary, as alternative embodiments mayperform the operations in a different order, combine certain operations,overlap certain operations, or the like. References in the specificationto a given embodiment indicate that the embodiment described may includea particular feature, structure, or characteristic, but every embodimentmay not necessarily include the particular feature, structure, orcharacteristic. Further, while given components of the system have beendescribed separately, one of ordinary skill will appreciate that some ofthe functions may be combined or shared in given systems, machines,devices, processes, instructions, program sequences, code portions, andthe like.

The techniques herein provide for improvements to another technology ortechnical field, namely, CAD/CAM systems, and dental implant planningsystems, as well as improvements to display technologies that are usedwith such systems.

Having described our invention, what we now claim is as follows:
 1. Adisplay method executing on a computing machine associated with animplant planning tool, comprising: rendering a 3D model of a physicalobject, the 3D model composed of connected triangles; rendering atexture superimposed on a surface of the 3D model, the texture beingrendered at a first time at a first contrast; and at a second time, andresponsive to receipt of data indicating positioning of a displaypointer at a given position on the 3D model, re-rendering the texture ina display area local to the given position at a second contrast that ishigher than the first contrast.
 2. The display method as described inclaim 1 wherein the texture is a monochrome image, or a color imageoverlaid on the 3D model.
 3. The display method as described in claim 1wherein the given position on the 3D model corresponds to a margin on adental preparation.
 4. The display method as described in claim 1wherein re-rendering the texture includes: identifying a set of 3Dvertices associated with the display area local to the given position;and capturing statistical data for the set of 3D vertices identified;and using the captured statistical data to generate one or more gaincontrol signals; and applying the one or more gain control signals torender the texture in the display area at the second contrast.
 5. Thedisplay method as described in claim 4 wherein the statistical dataincludes mean intensity and standard deviation of intensities for theset of 3D vertices.
 6. The display method as described in claim 4including filtering the captured statistical data.
 7. The display methodas described in claim 1 wherein positioning of a display pointer at agiven position on the 3D model results from moving a mouse cursor. 8.The display method as described in claim 1 wherein re-rendering thetexture includes adjusting an intensity of a set of display points basedon a statistical measurement.
 9. The display method as described inclaim 1 wherein the second contrast comprises a set of contrast values.10. The display method as described in claim 9 wherein the set ofcontrast values increases from a center to an edge of the display arealocal to the given position.